How to involve, motivate and sustain students in service learning programs

Version of RecordPublishe

Computational Methods for Pigmented Skin Lesion Classification in Images: Review and Future Trends

Skin cancer is considered as one of the most common types of cancer in several countries, and its incidence rate has increased in recent years. Melanoma cases have caused an increasing number of deaths worldwide, since this type of skin cancer is the most aggressive compared to other types. Computational methods have been developed to assist dermatologists in early diagnosis of skin cancer. An overview of the main and current computational methods that have been proposed for pattern analysis and pigmented skin lesion classification is addressed in this review. In addition, a discussion about the application of such methods, as well as future trends, is also provided. Several methods for feature extraction from both macroscopic and dermoscopic images and models for feature selection are introduced and discussed. Furthermore, classification algorithms and evaluation procedures are described, and performance results for lesion classification and pattern analysis are given

Collaborative discovery of Chinese neologisms in social media

2014 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2014, 5-8 October 2014The emergence of neologism in social media has bought the researchers' attention. Traditional ways of text mining are not sufficient to handle the unique properties of messages in the new media. New methods have been developed to extract neologisms in order to help researchers to understand about community behavior in different media. In this paper, we propose a collaborative framework to detect neologisms from various social media. There are 4 different types of agents working collaboratively. Among them, the summarizing agent is using the life span parameter to confirm if an unknown character pattern is a neologism. Preliminary experiments have been performed to investigate the possible popularity patterns of some known neologisms.Department of ComputingRefereed conference pape

Analyzing sentimental influence of posts on social networks

Lots of effort has been conducted to analyze information of social networks, such as sentiment trend analysis of social network users. Our aim is to analyze the sentimental influence of posts and compare the result on various topics and different social media platforms. Large amounts of posts are generated on social networks every day. People are curious in finding the influence among them. Most researchers measured the influence of a post through the number of replies it received. However, we are not sure if the influence is made positively or negatively on other posts if their sentimental information is not considered. In this paper, three research questions are raised and methodologies are proposed for the measure of sentimental influence of posts. Finally, a preliminary experiment is designed and carried out with some interesting results found.Department of ComputingRefereed conference pape

Supporting metasearch with XSL

Metasearch engines offer better coverage and are more fault-tolerant and expandable than single search engines. A metasearch engine is required to post queries with and obtain retrieval results from several other Internet search engines. In this paper, we describe the use of the extensible style language (XSL) to support metasearches. We show how XSL can transform a query, expressed in XML, into different forms for different search engines. We show how the retrieval results could be transformed into a standard format so that the metasearch engine can interpret the retrieved data, filtering the irrelevant information (e.g. advertisement). The proposed structure treats the metasearch engine and the individual search engines as separate modules with a clearly defined communication structure through XSL. Thus, the system is more extensible than coding the structure and syntactic transformation processes. It allows other new search engines to be included just through plug-and-play, requiring only that the new transformation of XML for this search engine be included in the XSL. © 2003 Elsevier Inc. All rights reserved

Automatic Template Detection for Structured Web Pages

Department of Computin

Predicting short interval tracking polls with online social media

The of behavioral patterns in online social media are often reflecting the happenings in our society. These patterns, which can be considered as opinions, are often correlated with public opinion polling. However, many correlation analyses done previously were for subsequent discoveries and not being able to handle short interval polling opinions. For opinions obtained from tracking polling with short opinion collection interval, like rolling polling, it cannot perform well in tracing the latest trends. This paper describes an extended correlation model for such kind of polling in examining the correlation between opinion in online social media and the public opinion from tracking poll. It has been tested with a recent rolling polling and it outperformed the previous correlation models.Department of ComputingRefereed conference pape

Microarray data classification based on computational verb

202002 bcrcVersion of RecordPublishe

Comprehensive evaluation of the MBT STAR-BL module for simultaneous bacterial identification and β-lactamase-mediated resistance detection in Gram-negative rods from cultured isolates and positive blood cultures

2017-2018 > Academic research: refereed > Publication in refereed journal201808 bcrcVersion of RecordPublishe

A Health App for Post-Pandemic Years (HAPPY) for people with physiological and psychosocial distress during the post-pandemic era : protocol for a randomized controlled trial

202406 bcchVersion of RecordOthersThe Health and Medical Research Fund (HMRF) - Commissioned Research on COVID-19 from the Health Bureau of Hong Kong Special Administrative RegionPublishedC